System For Target Online Advertising Using Biometric Information

ABSTRACT

An apparatus for providing customized advertisements includes a database that stores a plurality of electronic advertisements, receives biometric information of a client from at least one biometric device of the client, and receives receptivity information of the client responding to the plurality of electronic advertisements, as well as a processor that accesses the database, and maps the biometric information and the receptivity information and analyzes the mapped information to generate customized marketing data. The processor also calculates a receptivity probability for each of the plurality of electronic advertisements based on the customized marketing data by using current biometric state of the client, selects an electronic advertisement from the plurality of electronic advertisements based on the calculated receptivity probabilities, and outputs to the client the selected electronic advertisement.

TECHNICAL FIELD

The present teachings relate generally to a system for targetadvertising, and more particularly to a system for target onlineadvertising using biometric information.

BACKGROUND

Traditionally, it takes seven times to repeat a marketing message beforeaudiences register and accept the message. Further, social media targetadvertisements based merely on conversations. For example, Amazon maytarget ads based on verbal conversations that Alexa hears. Ads can alsobe targeted based on social media posts that a person writes and shares.There is a need to make target advertising more effective.

SUMMARY

The needs set forth herein as well as further and other needs andadvantages are addressed by the present teachings, which illustratesolutions and advantages described below.

It is an object of the present teachings to remedy the above drawbacksand shortcomings associated with known marketing systems.

It is also an object of the present teachings to provide effectivetargeted advertising by taking into account when audiences are receptiveto advertisements in general or advertisements for particular productsor services, and/or receptive to particular forms of advertisements.

It is another object of the present teachings to provide effectivetargeted advertising that cuts through the “noise” of otheradvertisements and thus increases the potential for getting a person'sattention. The term “noise” has a negative connotation in marketing andmeans anything that distracts an audience member from receiving amessage being conveyed in a marketing campaign. Promotional clutter is amajor issue in that a person tires of it and has a difficult timeremembering specific messages.

It is another object of the present teachings to provide improved targetadvertising by utilizing biometric information of audience members.

These and other objects of the present teachings are achieved byproviding an apparatus and/or system that targets advertisements toaudiences by utilizing their biometrics, for example but not limited totheir heartbeat, sleep patterns, steps walked or ran, location, waterintake, food intake, etc. The apparatus uses biometric information on anaudience member to gauge emotional and/or physiological receptivitytoward marketing messages (e.g., brand messages). For instance, theapparatus looks at one or a combination of: a person's heart rate(current as compared to base), sleep pattern, steps walked/jogged/randuring the day, water intake, and/or food intake, in order to determinewhen advertising is most effective for that person. The biometricinformation may also be paired with the person's emotions as detectedand assessed by facial recognition technology in order to provideoptimum target advertising that is personalized to the person's currentmood.

The present teachings provide an apparatus comprising a database storinga plurality of electronic advertisements (e.g., Internetadvertisements), receiving biometric information of a client from atleast one biometric device of the client, and receiving receptivityinformation of the client responding to the plurality of electronicadvertisements, as well as a processor accessing the database, mappingthe biometric information and the receptivity information, and analyzingthe mapped information to generate customized marketing data,calculating a receptivity probability for each of the plurality ofelectronic advertisements based on the customized marketing data byusing current biometric state of the client, selecting an electronicadvertisement from the plurality of electronic advertisements based onthe calculated receptivity probabilities, and outputting to the clientthe selected electronic advertisement.

Other teachings of the apparatus, system and method are described indetail below and are also part of the present teachings.

For a better understanding of the present teachings, together with otherand further aspects thereof, reference is made to the accompanyingdrawings and detailed description, and its scope will be pointed out inthe appended claims. The summary is not intended to limit the scope ofthe present teachings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a system according to the present teachings.

FIG. 2 depicts data flow of a system according to the present teachings.

DETAILED DESCRIPTION

The present teachings are described more fully hereinafter withreference to the accompanying drawings. The following description ispresented for illustrative purposes only and the present teachingsshould not be limited to these embodiments. Any computer configurationand architecture satisfying the speed and interface requirements hereindescribed may be suitable for implementing the system and method of thepresent embodiments.

In compliance with the statute, the present teachings have beendescribed in language more or less specific as to structural andmethodical features. It is to be understood, however, that the presentteachings are not limited to the specific features shown and described,since the systems and methods herein disclosed comprise preferred formsof putting the present teachings into effect.

For purposes of explanation and not limitation, specific details are setforth such as particular architectures, interfaces, techniques, etc. inorder to provide a thorough understanding. In other instances, detaileddescriptions of well-known devices, circuits, and methods are omitted soas not to obscure the description with unnecessary detail.

Generally, all terms used in the claims are to be interpreted accordingto their ordinary meaning in the technical field, unless explicitlydefined otherwise herein. All references to a/an/the element, apparatus,component, means, step, etc. are to be interpreted openly as referringto at least one instance of the element, apparatus, component, means,step, etc., unless explicitly stated otherwise. The steps of any methoddisclosed herein do not have to be performed in the exact orderdisclosed, unless explicitly stated. The use of “first,” “second,” etc.for different features/components of the present disclosure are onlyintended to distinguish the features/components from other similarfeatures/components and not to impart any order or hierarchy to thefeatures/components.

The present teachings disclose a system, a computer implemented method,an apparatus, and computer useable program product for providingcustomized Internet advertisements (or targeting online or in-appadvertising) to a client. The system may have a database for storing aplurality of Internet advertisements and corresponding campaigninformation.

An electronic device according to the present teachings may include atleast one of, for example, a desktop personal computer (PC), a laptopPC, a tablet PC, a smart phone, a mobile phone, a video phone, an e-bookreader, a netbook computer, a workstation, a server, a personal digitalassistant (PDA), a portable multimedia player (PMP), an MP3 player, amobile medical device, a camera, a camcorder, or a wearable deviceincluding at least one of an accessory-type wearable device (e.g., awatch, glasses, or a head mounted device (HMD)), a textile/clothingintegrated wearable device (e.g., electronic clothing), or abody-implantable wearable device (e.g., implantable circuit), but notlimited thereto.

A biometric device according to the present teachings may include atleast one of, for example, a desktop PC, a laptop PC, a tablet PC, asmart phone, a e-book reader, a smart watch, an activity tracker, a PDA,a PMP, an MP3 player, a mobile medical device, a camera, a camcorder, asmart home system including a center control hub and Internet of Things(IOT) devices such as a refrigerator, a water filtration system, atoilet, a mirror, a home security system (e.g., a doorbell, a lock, or acamera), a light switch, a temperature controller, an air quality system(e.g., a monitor or an alarm), but not limited thereto. For example, thelaptop or smartphone may access a camera or a microphone thereof torecognize and collect data based on facial recognition, voicerecognition, iris recognition, fingerprint, age analysis, and anydemographic information. The laptop or smartphone may track the client'sonline behavior by using a “cookie.” The smart watch or activity trackermay recognize and collect data based on sleep, travel, steps, heartrate, height, weight, and other personal biometrics. The smart watch oractivity tracker may also track the client's location and gatherinformation regarding the proximation and geographic optimization of theclient's location. The refrigerator may detect the type of items storedin it such as food or beverage and keep track of the usage (consumption)and expiry (throwing away) of such items. The water filtration systemmay detect the water consumption. The toilet may detect urine andperform urine analysis. The mirror may include sensors that detect veinand skin conditions, such as dehydration. Other biometric informationthat may also be gathered by the biometric devices include eye movement,body temperature, breathing pattern, etc. In some embodiments, thebiometric device may comprise hardware that detects and/or measuresparameters representative of physiological, chemical, or behavioralcharacteristics of a person. Examples of the hardware include, but arenot limited to, high-quality and robust touch/tactile sensors, heartrate sensors, cadence sensors (e.g., typing cadence sensors that measurekeystroke dynamics, including speed, length of time between consecutiveletters typed, and degree of impact on the keyboard; cycling cadencesensors that measure energy output in the form of rotations per minute),and GPS sensors for determining a person's location, altitude, velocity,etc. Signature recognition hardware may be used in and/or with abiometric device. For instance, static signature recognition hardwaremay comprise an optical scanner or camera that digitizes a signature(previously written on paper) and runs an algorithm that recognizes aperson's text by way of analyzing its shape, center of gravity, edgesand curves. Dynamic signature recognition hardware may comprise agraphics tablet or motion-sensitive stylus (e.g., stylus with inertialsensor) that acquires the person's handwriting in real-time and analyzethe dynamically captured direction, stroke, pressure, and shape of theperson's signature, thereby enabling reliable indication of the person'sidentity. In other embodiments, the biometric device may include afingerprint sensor, finger recognition sensor, compact sensor that isconfigured to detect and store millions of repeated fingerprintreadings, palm vein recognition sensor, ear recognition sensor, irisrecognition and retina recognition sensor (e.g., near infrared cameratechnology), facial recognition system that measures multiple datapoints of a face, or voice recognition system that determines theidentify of a speaker for accessing control. An accelerometer,gyroscope, compass, ambient light sensor, heartbeat sensor (e.g.,optical heartbeat sensor), altimeter, and walk gait recognition systemare other hardware components that may be incorporated into thebiometric device for detecting characteristics of a person.

The platform according to the present teachings may include hardware,such as a computer or a server, or components thereof. The platform mayprovide an environment in which a piece of software is executed, such asa web page, an application, or a remote desktop.

When a client opens a website and sees an Internet advertisementprovided by the system on the website, the client may click the Internetadvertisement. If it is the first time this client clicks any Internetadvertisement provided by the system, the system may output a messageasking whether the client would like to opt in to provide biometricinformation assessed from biometric devices to the system to get acustomized online advertising service.

If the client chooses to opt in, the system may ask the client to createan account by providing basic information such as user name and passwordand setting up the biometric devices. The system may detect anybiometric devices nearby and provide a list of the detected biometricdevices to the client so that the client can choose the biometricdevices which belong to or are associated with the client and whichshould transmit the client's biometric information to the system.Alternatively, the system may use available information from any IOT andwearable device management system(s) provided by a third party togenerate a list of the client's biometric devices, and allow the clientto choose from that list.

After the initial opt-in setup of the biometric devices of the client,the system may receive biometric information or data of the client fromthe biometric devices of the client and store it in the database. Thebiometric information is data describing at least one of a plurality ofphysiological characteristics and behavioral characteristics of thecustomer, and the biometric information is gathered in real-time fromany of the biometric devices of the client.

After the initial setup, when the client again opens a website, thesystem may collect receptivity information of the client responding tothe Internet advertisement provided with the website. The receptivityinformation may include at least one of the number of click-throughsfrom the Internet advertisement, the number of purchasing eventsoccurred from the Internet advertisement, or emotional characteristicsof the client when viewing the Internet advertisement. For example, thesystem may count the number of click-throughs from the Internetadvertisement, or the system may further track the client's onlineactivity to check whether the client made a purchase after clickingthrough the Internet advertisement. As another example, the website maytrack the client's online activity through website cookies, includingthe number of click-throughs from the Internet advertisement and/orpurchase events occurred due to the Internet advertisement, and thewebsite may send the tracked activity information to the system. Asanother example, the system may monitor, through a camera, the client'sfacial expression or eye movement when the client opens a website torecord the emotional characteristics of the client, and detect, at thesame time, whether the client sees or clicks through the Internetadvertisement. The system may receive and store the receptivityinformation of the client responding to the plurality of Internetadvertisements. In some embodiments, the receptivity information may beobtained and/or derived from tracking URLs, which are normal URLs with atracking token (UTM parameter) added to the end of it. When a clientclicks on the tracking URL, the UTM parameter sends a signal indicatingthat the URL was clicked. In addition or alternatively, the receptivityinformation may be obtained and/or derived from tracking pixels (likeFacebook Pixel). The tracking pixel is a 1 px by 1 px image that isplaced in a display ad or on a webpage. When the tracking pixel loads,it sends a signal indicating that a client viewed the page. When used inconjunction with click-through data, tracking pixel data can providefurther insight into receptivity. For example, if a banner ad with atracking pixel is used, the system can analyze whether the client justviewed or actually clicked on the ad and thus evaluate how successfulthe ad is.

The system may include a processor that can access the database for thebiometric information and the receptivity information. The processor maymap the receptivity information to the biometric information, e.g.,based on time. For example, when an amount of sleep is detected over thenight, the receptivity information for the next day will be mapped tothe biometric information of the sleep parameters of the night. Then,the processor may analyze the mapped information to generate customizedmarketing data. The customized marketing data may establish a relationbetween a receptivity probability for each of the plurality of Internetadvertisements and a plurality of parameters representing the biometricinformation of the client. The customized marketing data may be in theform of a graph, or in the form of an equation, although not limitedthereto. As in the sleep example, a graph of the customized marketingdata may be established with sleep amount as X-axis and receptivity of acertain Internet advertisement as Y-axis.

The processor may calculate a receptivity probability for each of theplurality of Internet advertisements based on the customized marketingdata by using current biometric state. The current biometric state maybe the most recently received biometric information of the client over acertain time period, or real-time biometric information. For example, ifthe client had a certain amount of sleep last night, the receptivityprobability for a certain Internet Advertisement is calculated as apoint on Y-axis corresponding to the certain amount of sleep on X-axisbased on the graph of the customized marketing data.

The processor may select an Internet advertisement from the plurality ofInternet advertisements based on the calculated receptivityprobabilities and output to the client the Internet advertisementthrough the client's electronic device. For example, if the calculatedreceptivity probability for Internet Advertisement 1 is 0.2, and thecalculated receptivity probability for Internet Advertisement 2 is 0.8,the processor will select Internet Advertisement 2 between these twoadvertisements and transmit it to client through the client's electronicdevice. In some embodiments, the selected Internet advertisement has areceptivity probability greater than 0.70, and preferably greater than0.80, and more preferably greater than 0.90.

Referring to FIG. 1 , an advertising (or marketing) system 100 accordingto the present teachings may include a database 103, a learningprocessor 104, and an administration server 105. The administrationserver 105 may further include a cluster (or compiling) module 106. Allmain components can be located on different machines in differentphysical locations, or even run on a single machine. The advertisingsystem 100 interacts with a client's electronic device 115 such as butnot limited to a system on which standard Web browser software runs. Theclient's electronic device 115 first interacts with a web or app server(not shown) to get the access to the service provided by the advertisingsystem 100. The advertising system 100 also interacts with a client'sbiometric devices upon authorization to get biometric information of theclient. In addition, the advertising system 100 interacts with anadvertiser system 130 such as but not limited to a system that providesa plurality of Internet advertisements and corresponding campaigninformation. The client's biometric devices 110, the client's electronicdevice 115, and the advertiser system 130 are connected to theadministration server 105, which offers access to the database 103.

The administration server 105 handles initial requests for opt-in andrequests from clients to deliver customized advertisements. Theadministration server 105 also handles the receptivity records ofadvertisements. The cluster module 106 in the administration server 105collects biometric information of the client from the client's biometricdevices upon authorization from the client. The administration server105 contacts the database 103 in order to save and obtain the datarelevant to provide the advertising service.

The administration server 105 also controls the access to the database103 by the learning processor 104. The learning processor 104 mayperform machine learning by mapping the biometric information and thereceptivity information and analyzing the mapped information to generatecustomized marketing data for each client. The learning processor 104periodically queries the files from the database 103 to obtainreceptivity records of advertisements and biometric information of theclient and adjusts a set of display weights accordingly. These weightsare stored in the database 103, where the administration server 105 canaccess it during advertisement selection.

Upon a request for the service from the client through the client'selectronic device 115, the administration server 105 calculates, basedon the customized marketing data generated by the learning processor104, a receptivity probability for each of the plurality of Internetadvertisements as an output, by using current biometric state of theclient as an input. The administration server 105 selects an Internetadvertisement from the plurality of Internet advertisements based on thecalculated receptivity probabilities, for example, selects the Internetadvertisement with the largest receptivity probabilities. Theadministration server 105 outputs the selected Internet advertisementthrough the client's electronic device.

Referring to FIG. 2 , an advertising platform 200 according to thepresent teachings may include databases 203, a learning processor 204,an administration server 205, and a cluster module 206. The advertisingplatform 200 may provide functionality for targeting advertisements. Theadvertising platform 200 includes a number of additional modulesproviding additional functionality(ies), and may be part of the samesoftware program or different software programs operating on differentmachines.

The databases 203 may include a database for storing a plurality ofInternet advertisements and corresponding campaign information, adatabase for storing biometric information for each client, a databasefor storing receptivity records of advertisements for each client, adatabase for customized marketing data for each client resulted frommachine learning based on the biometric information and the receptivityrecords.

The client's biometric device(s) 210 may include, for example, aclient's electronic device 215, a smart home hub 244, a refrigerator245, a water filtration system 246, a toilet 247, and a mirror 248. Theclient's electronic device(s) 215 may include a personal computer 241, asmart phone, a smart watch and/or activity tracker 243.

A client may use his electronic device 215 to establish a secureconnection over the Internet and log on to the advertising platform 200.The advertising platform 200 may be offered as a service for deliveringan advertisement or marketing message to the client. The advertisingplatform 200 may be provided through secure web pages, using anapplication, or even as a secure remote desktop connection, although notlimited thereto. For example, a client opens a webpage on his computerand clicks a banner ad provided as the advertising service.

By logging on to the advertising platform, the client's electronicdevice 215 sends an initial request for the advertising service 221. Theadvertising platform 200 responds with a message for creating an accountfor the advertising service or for using an existing account of a thirdparty for the advertising service, and sends the response 222 to theclient's electronic device 215. The message asks whether the clientwould like to opt in a service that allows the advertising platform toaccess his biometric information collected by his biometric devices 210and delivers customized advertisement using his biometric information.If the client chooses to opt in for the service, the advertisingplatform 200 may further ask the client to set up the biometric devices.For example, the advertising platform 200 may get or detect a list ofdevices and ask the client to choose which biometric devices areassociated with the client and which of these devices the client wantsthe biometric information to be transmitted to the advertising platform.

The client's electronic device 215 selects to opt in and selects thebiometric devices, and provides the information 223 for setting up anaccount including the selected biometric devices. Additional steps maybe required to get authorization for each of the selected biometricdevices, for example, from the biometric device's end or from a hubsystem managing the biometric devices. The administration module 205 mayprocess the above information 223 and allow the cluster module 206 togather the biometric information in real-time accompanying the relatedinformation regarding gathering. The biometric information is datadescribing at least one of a plurality of physiological characteristicsand behavioral characteristics of the client, and it also includes timeinformation and device information of the biometric data when gatheredby the cluster module 206.

The cluster module 206 may send a request for biometric data and relatedinformation 224 to the client's biometric devices 210. The client'sbiometric devices 210 may send the requested information 225 to thecluster module 206. The cluster module 206 may save the biometric dataand related information to the databases 203.

The administration module 205 or the cluster module 206 may collectreceptivity records of advertisements of a client. For example, when theclient browses a webpage or uses an App, the browser or the App maytrack online activity including viewing history or purchase history andmay record receptivity of advertisements. The administration module 205or the cluster module 206 may send a request for receptivity record ofadvertisements and related purchase history 226 to the client'selectronic device 215. The client's electronic device 215 may send therequested data 227 to the administration module 205 or the clustermodule 206. The administration module 205 or the cluster module 206 maysave the receptivity data to the databases 203.

The learning processor 204 may access the databases 203 for thebiometric data and the receptivity data. The learning processor 204 mayanalyze the data to generate customized marketing data for each clientbased on the biometric data and receptivity data. The customizedmarketing data for each client establishes a relation between biometricstatus and receptivity for each advertisement.

The administration module 205 may receive Internet advertisements or/andonline campaign information 231 from advertisers' system 230periodically, and save them to the databases 203. The learning processor203 may also get access to the advertisement information for generatingthe customized marketing data for each client.

When the client's electronic device 215 establishes a secure connectionover the Internet and logs on to the advertising platform 200 again, itsends a request for delivering the customized advisement(s) 228 to theadvertising platform 200. For example, a client opens a webpage, whichis accompanied with the online advertising service provided by theadvertising platform 200, on the computer. By opening the webpage, theclient's electronic device 215 sends a request for the onlineadvertising service.

The administration module 205 may use the customized marketing data forthe client and select an Internet advertisement from the plurality ofInternet advertisements saved in the databases 203 based on the client'scurrent biometric status. The administration module 205 may send theselected Internet advertisement 229 to the client's electronic device215.

While the present teachings have been described above in terms ofspecific embodiments, it is to be understood that they are not limitedto these disclosed embodiments. Many modifications and other embodimentswill come to mind to those skilled in the art to which this pertains,and which are intended to be and are covered by this disclosure. It isintended that the scope of the present teachings should be determined byproper interpretation and construction of the disclosure and its legalequivalents, as understood by those of skill in the art relying uponthis specification and the attached drawings.

What is claimed is:
 1. An apparatus for providing customizedadvertisements, the apparatus comprising: a database, storing aplurality of electronic advertisements, receiving biometric informationof a client from at least one biometric device of the client, receivingreceptivity information of the client responding to the plurality ofelectronic advertisements; and a processor accessing the database,associating the receptivity information to the biometric information,and analyzing the associated information to generate customizedmarketing data, identifying a receptivity probability for each of theplurality of electronic advertisements based on the customized marketingdata by using current biometric state of the client, selecting anelectronic advertisement from the plurality of electronic advertisementsbased on the identified receptivity probabilities, and transmitting theselected electronic advertisement to a client electronic device whereinprior to the database receiving the biometric information and receivingthe receptivity information, the processor is configured to: prompt theclient to opt-in to receive customized advertising; in response to theclient accepting to receive customized advertising, detect the at leastone biometric device in proximity to the client electronic device; andreceive client input which indicates that the at least one biometricdevice belongs to or is associated with the client.
 2. The apparatus ofclaim 1, wherein the biometric information includes data representing atleast one physiological characteristic or behavioral characteristic ofthe client, and wherein the biometric information is gathered inreal-time.
 3. The apparatus of claim 1, wherein the database receives aportion of the receptivity information from a tracking URL associatedwith one of the plurality of electronic advertisements.
 4. The apparatusof claim 1, wherein the database receives a portion of the receptivityinformation from a tracking pixel contained in one of the plurality ofelectronic advertisements.
 5. The apparatus of claim 1, wherein thereceptivity information includes at least one of a number ofclick-throughs from the electronic advertisements or a number ofpurchasing events from the electronic advertisements.
 6. The apparatusof claim 1, wherein the receptivity information includes emotionalcharacteristics of the client when viewing the electronicadvertisements.
 7. The apparatus of claim 1, wherein the processorgenerates the customized marketing data by determining a relationbetween a receptivity probability for each of the plurality ofelectronic advertisements and a plurality of parameters representing thebiometric information of the client, and wherein the current biometricstate of the client includes at least one of the plurality of parametersrepresenting the biometric information of the client in real time ormost recently received.
 8. The apparatus of claim 1, wherein theprocessor detects a plurality of biometric devices and provides a listof the detected biometric devices to the client, and wherein theprocessor receives client feedback indicating which of the plurality ofbiometric devices are associated with the client and should transmit thebiometric information of the client to the database.
 9. The apparatus ofclaim 1, wherein the processor associates the biometric information andthe receptivity information based on time.
 10. The apparatus of claim 9,wherein the biometric information received by the database includes anamount of sleep that the client received the night before, and whereinthe processor associates the receptivity data of the following day tosleep parameter of the night before.
 11. The apparatus of claim 9,wherein the biometric information includes heartbeat data, sleep patterndata, steps taken by the client, location data, water intake data,and/or food intake data.
 12. The apparatus of claim 1, wherein theprocessor selects the electronic advertisement having the highestreceptivity probability among the plurality of electronicadvertisements.
 13. A system for providing customized advertisements toa client, the system comprising: an advertising platform having adatabase, a processor, and an administration module, the advertisingplatform configured to interact with a client electronic device and aclient biometric device; a plurality of advertiser systems incommunication with the advertising platform, each advertiser systemcontaining at least one electronic advertisement of an advertiser; inresponse to client authorization, the database receives biometricinformation of the client from the client biometric device and receivesreceptivity information of the client responding to a plurality ofelectronic advertisements; the processor associates the receptivityinformation to the biometric information and analyzes the associatedinformation to generate customized marketing data; the administrationmodule identifies a receptivity probability for each of the plurality ofelectronic advertisements based on the customized marketing data byusing current biometric state of the client and selects an electronicadvertisement from the plurality of electronic advertisements based onthe identified receptivity probabilities; and the advertising platformtransmits the selected electronic advertisement to the client electronicdevice; wherein prior to the database receiving the biometricinformation and receiving the receptivity information, theadministration module is configured to: prompt the client to opt-in toreceive customized advertising; in response to the client accepting toreceive customized advertising, detect the client biometric device inproximity to the client electronic device; and receive client inputwhich indicates that the client biometric device belongs to or isassociated with the client.
 14. The system of claim 13, wherein theadministration module is connected to the advertiser systems andprovides access between the database and the advertiser systems.
 15. Thesystem of claim 13, wherein the processor utilizes machine learning toassociate the biometric information and the receptivity information. 16.The system of claim 15, wherein the processor obtains receptivityinformation and biometric information to adjust a set of weights,wherein said weights are used in selecting the electronic advertisement.17. The system of claim 13, wherein the selected electronicadvertisement has the highest identified receptivity probability. 18.The system of claim 17, wherein the biometric information includes datarepresenting at least one physiological characteristic or behavioralcharacteristic of the client, and wherein the biometric information isgathered in real-time.
 19. A method of providing customizedadvertisements to a client, comprising: obtaining biometric data of theclient from at least one biometric device of the client; transmittingthe biometric data to a database of an advertising platform for storage;collecting receptivity information of the client responding to one ormore electronic advertisements, which are displayed on an electronicdevice of the client; transmitting the receptivity information from theelectronic device to the database for storage; associating, via aprocessor of the advertising platform, the receptivity information tothe biometric data to generate customized marketing data; obtaining arecent biometric state of the client from the at least one biometricdevice and using the recent biometric state to identify a receptivityprobability for each of a plurality of electronic advertisements basedon the customized marketing data; selecting one of the plurality ofelectronic advertisements which has the highest receptivity probability;and transmitting the selected electronic advertisement to the client;wherein prior to the steps of obtaining the biometric data andcollecting the receptivity information, the method comprises: promptingthe client to opt-in to receive customized advertising in response tothe client accepting to receive customized advertising, detecting the atleast one biometric device in proximity to the electronic device; andreceiving client input which indicates that the at least one biometricdevice belongs to or is associated with the client.
 20. The method ofclaim 20, wherein the biometric information includes data representingat least one physiological characteristic or behavioral characteristicof the client, and wherein the biometric information is gathered inreal-time.